Genome Wide Association Study to predict severe asthma exacerbations in children using random forests classifiers.

ABSTRACT:

Background

Personalized health-care promises tailored health-care solutions to individual patients based on their genetic background and/or environmental exposure history. To date, disease prediction has been based on a few environmental factors and/or single nucleotide polymorphisms (SNPs), while complex diseases are usually affected by many genetic and environmental factors with each factor contributing a small portion to the outcome. We hypothesized that the use of random forests classifiers to select SNPs would result in an improved predictive model of asthma exacerbations. We tested this hypothesis in a population of childhood asthmatics.

Methods

In this study, using emergency room visits or hospitalizations as the definition of a severe asthma exacerbation, we first id

SUBMITTER: Xu M 

PROVIDER: S-EPMC3148549 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature